1. Field of the Invention
The present invention relates to a method and system for commissioning industrial plants, in particular in the basic materials industry, having a plant control system which carries out both non-control functions and control functions and whose control system operates with process models, in particular control engineering models, for example in the form of mathematical models, neural network models, expert systems etc., in a control system computing unit
2. Description of the Prior Art
In the control of industrial plants, in particular plants which proceed with very rapid processes, very slow processes, processes which run in leaps and bounds, or processes do for which there is no suitable state sensors, operations are mostly carried out using control engineering models. As a rule, such plants have a basic automation system and a process management system (non-control and control). Experience shows that the commissioning of relatively large plants is very time-consuming and costly and requires specialists who are experienced in plant engineering. This also applies to the control engineering plant design and to the control project engineering of the individual components.
It is an object of the present invention, for plants of the type outlined above, in particular for plants in the basic materials industry, but also for plants in the chemical industry and for producing electrical power, to specify a commissioning method and a system suitable for this with which, given an optimum commissioning result, a reduction in time and costs can be achieved. In this case, the continuous operation of the plant which has been commissioned is intended to be able to be subsequently continually improved, and easily evaluable knowledge for the control project engineering and the design of corresponding plants are to be obtained. In summary, the aim can be described as reducing the engineering costs with a simultaneous improvement in the plant function.
The objects achieved in that the commissioning is carried out subdivided fashion into commissioning the non-control functions, with extensive initialization of the control functions, by means of personnel located on site, and extensive commissioning of the control functions by means of remotely-transmitted data via data lines from at least one site remote from the plant, preferably from an engineering center. As a result of this subdivision of the commissioning into a so-called basic commissioning is and an engineering commissioning, it is advantageously possible to dispense with having to use control engineering specialists, in particular specialists for the setting of parameters and improvement of control engineering models, on site. The commissioning costs thus can be reduced considerably. Furthermore, the commissioning can be carried out more rapidly and more reliably since, for the engineering commissioning, a specialist team can be made available to whom all the aids of an engineering center and external consultants are available.
It is already known to equip PCs by means of programs which are input into the PC via data transmission. Furthermore, the diagnosis of PCs as well as of individual automation devices, such as machine-tool controllers or programmed logic controllers, for example, is known. The known procedure for the equipment, diagnosis and functional improvement of individual devices cannot, however, be transferred to the commissioning of entire plants, in particular entire plants which are as complex as those in the basic materials industry. For this purpose, learning routines are just as necessary as the use of the computing intelligence of the plant, long access times and a dialog in the sense of xe2x80x9ctrial and errorxe2x80x9d. This was previously held to be impossible to implement to the extent necessary.
In a refinement of the present invention, it is contemplated that engineering optimization is carried out while commissioning the control functions. The optimization is preferably carried out xe2x80x9cstep by stepxe2x80x9d under remote influence in at least one control system computing unit of the plant. That is, the individual optimization steps run on a computing unit of the process control system so as to avoid those problems which can result in the case of taking over an optimization step carried out on an external computing unit into the computing unit of the control system. From the point of view of the complexity of the programs in the plant control systems, software errors would otherwise always be expected in taking over optimized program parts. The avoidance of implementation problems is a considerable advantage of the system according to the present invention.
In addition to remote commissioning, remote functional improvement and remote optimization of the control part, provision is also made a remotely-influenced improvement of the non-control part. Even the basic automation of an industrial plant is so complex nowadays that the remote optimization according to the present invention is worthwhile. In this case, the appropriate level of the plant control system is advantageously used.
Following the commissioning of the control functions with the initial optimization, a further improvement of plant operation is carried out continuously by means of engineering optimization with the aid of the engineering center. It is thus ensured that the plant is further operated in an optimum manner in control engineering terms. This is important, in particular, in the case of changes in the product program; for example, as the result of accepting further material grades into the product program.
The optimization relates, in particular, to setting parameters for models, such as those in the form of algorithms or artificial neural networks (ANN), and to further development of the algorithms of the models or of the design of the ANN, and of expert knowledge evaluated by computer; for example, in the form of limiting curves, etc. Thus, the most important modules of a model-based controller can be continuously improved in order to achieve optimum plant behavior.
Provision is advantageously made that, in the case of using neural networks as process models, the adaptation takes place in parallel with network training. Thus, account is taken particularly well according to the present invention of the properties of artificial neural networks (ANN). They are always in the state which is most advantageous for the optimization. It is furthermore of particular advantage if the artificial neural networks (ANN) are used for the improvement of algorithms and/or models, and if in so doing a closed loop is formed which is designed as a directly closed loop in a control system computing unit or as a loop which is closed indirectly via the engineering center. In particular, the loop which is closed via the engineering center in this case ensures that the newest control knowledge and computing knowledge can always be included in the optimization and improvement of parameters and/or models. In this case, it is advantageously also provided that the further development of models is carried out with the aid of an evolution strategy, for example via genetic algorithms. It is thus also possible for any necessary further devel the models to optimize the plant behavior and, if appropriate, also to optimize the plant itself.
In order to carry out the method in an advantageous manner, a commissioning or plant operational improvement system is provided which has at least one engineering center installed remote from the plantxe2x80x94in particular a commissioning and/or operational improvement centerxe2x80x94which is connected via remote data transmission means to at least one control system computing unit of a plant which is to be commissioned in engineering terms or to be improved further in engineering terms. By this means, the advantages of the method of the present invention may be achieved.
In an embodiment of the present invention, it is provided that THE system has, in an engineering center, an internal network which is preferably equipped as an Ethernet with twisted-pair connections, having at least a 10 megabit per second transmission speed, which preferably operates according to the TCP-IP protocol. This results in a secure internal network which can be implemented in a cost-effective manner and which has all the properties which are necessary for a remote commissioning and optimization center. The system furthermore has a remote commissioning or operational improvement network connected to the internal network for communication with industrial plants which has known, conventional data transmission components (ISDN, telephone, modem, Internet connections) and is connected to the engineering center by means of at least one security data transfer device (firewall). Thus, using conventional cost-effective components, the construction of a remote commissioning network, which has a construction necessary for reliable operation of the plant and for defense against operational espionage actions etc., is possible.
In an embodiment, the system has, in the region of the engineering center, external sites, for example project offices, which are physically separate but connected in terms of data, for example via ISDN lines, to said center and, together with the latter, form the engineering expertise. The discussion and/or solution of optimization tasks by external specialist personnel is thus possible whose teams, etc. are included in the engineering expertise. In this case, the cooperation of completely different teams is possible.
In a further embodiment of the present invention, it is provided that the commissioning or operational improvement center has an administrator unit, in particular having evaluation software for collected data, and is simultaneously designed to be suitable for logbook maintenance. For the purpose of optimization, in particular of operating points and specific operational steps, it is necessary to track the effects of control interventions in the case of earlier optimization measures. This is advantageously possible by means of the method according to the present invention.
For ISDN and Internet connections, there are routers provided which set up the desired connections. With the aid of these routers, which optionally operate automatically, the connection which is optimum in each case can be set up for the dialog between the operators of the individual plant components and the components of the engineering center, and for the connection between the individual computing units. Depending on the day of the week and the time of day, these may be different.
In order to carry out the present invention, there are in the control system of the plant computing engineering modules, a data collection unit etc., and in the center personnel with engineering knowledge, databases for the respective clients, general and client-specific engineering modules, in particular in a form which can be input like modules into the plant control system. Stepwise improvement with simple input of the new data into the overall system is thus possible.
Provided in the plant control system are computing devices for the adaptation of plant-specific parameters, for the storage of models designed specifically for the plant, for the storage of prior calculation algorithms, for the storage of trend sequences and for the storage of adaptation algorithms. The plant control system is thus able to carry out the engineering optimization in accordance with the predefinitions of the engineering center.
Provision is also made that for neural networks such as are often used for example in rolling mills or in electric-arc ovens, that is to say in the basic materials industry, optimization and training are carried out in parallel. For this, specifically designed software modules are present. Likewise, diagnostic memories and further computing devices are required for the engineering optimization of the plant. These software-controlled computing devices can be influenced via the data transmission means which are used in accordance with the present invention.
The hardware and software devices of the commissioning or operational improvement center include both nonspecific hardware devices, software tools, commissioning tools, software development tools, software evolution tools, ANN training tools, statistical evaluation programs, etc. and also special plant-specific software tools. Recourse is made as far as possible to plant-neutral modules wherein plant-specific and specially developed modules are only used when it is necessary.
The communication and optimization system for plant engineering optimization which is present according to the present invention is, in particular, designed to be capable of dialog and advantageously has, optical acquisition components both for the personnel handling it and for the plant parts optimized or to be diagnosed. It is therefore possible for optimization proposals, change proposals, diagnoses etc. to be carried out in a manner which largely corresponds to the presence of the specialists on site. It is, therefore, no longer personnel who travel but information. The commissioning center and the plant, as well as the plant control station, therefore advantageously have monitors and cameras. The same applies to external sites of the engineering center, for example project offices or specific software development units, so that it is actually possible to operate as though all the personnel involved in the optimization and the further development were located at one site, in particular at the site of the plant. This is of considerable advantage, in particular when working with artificial neural networks (ANN, as well as neuro-fuzzy and fuzzy applications), in which uniform handling is necessary from the collection of the training data up to the output of new parameters.